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DerChris2011

LightBurn MCP

by DerChris2011

get_cuts

Lists the cut layers and their settings in the open project, returning each entry's index so you can look up or update a specific cut.

Instructions

Requires capability "project". Cut settings of the project. LightBurn returns a fixed list: 30 cut layers, 2 tool layers, 1 internal entry, then 30 image cuts; MillMage returns its operation list. Each entry's index is the value to pass to get_cut / update_cut. Compact mode returns the core fields only (speed, min/max power, passes, mode, profile); use compact=false or get_cut for every field. Values use the user's display units (see get_units).

Input Schema

NameRequiredDescriptionDefault
compactNoCore fields only (default true). LightBurn only; MillMage entries are always returned in full.
in_use_onlyNoOnly entries that shapes actually use (default true).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does real work: it discloses the required 'project' capability, the fixed/known response shapes per backend, the meaning of 'index', and that values are in user display units. It stops short of stating that the call is read-only, the cost of the call, or what happens with an empty project.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Information is front-loaded: the prerequisite capability comes first, then what is returned, then how to widen the field set. It is dense but every sentence adds usable context; the one weak spot is that the LightBurn layer-count enumeration is wordy relative to its value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description compensates by describing the return structure, entry semantics, and field-level differences between compact and full mode. An agent can call this correctly and know how to consume the result without further lookup.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameters are already documented and the baseline is 3. The description's compact-mode note largely restates the schema, and it adds nothing about in_use_only, so it does not exceed the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the exact resource (the project's cut settings list) and what it contains, including the backend-specific structure (LightBurn's 30 cut layers / 2 tool layers / 1 internal entry / 30 image cuts vs. MillMage's operation list). It explicitly distinguishes itself from get_cut, update_cut, and get_units by naming each and their relationship.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It routes the agent clearly: 'use compact=false or get_cut for every field' gives a concrete alternative with a condition. It does not cover when not to use this tool (e.g., when only a single known index is needed), and it never explains the effect of the defaulted in_use_only filter, so guidance is strong but not exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.